OpenRaiser/Intern-Atlas huggingface dataset:
First-Take-All: Temporal Order-Preserving Hashing for 3D Action Videos
Venue: arXiv cs.CV 2015
Year: 2015

With the prevalence of the commodity depth cameras, the new paradigm of user interfaces based on 3D motion capturing and recognition have dramatically changed the way of interactions between human and computers. Human action recognition, as one of the key components in these devices, plays an important role to guarantee the quality of user experience. Although the model-driven methods have achieved huge success, they cannot provide a scalable solution for efficiently storing, retrieving and recognizing actions in the large-scale applications. These models are also vulnerable to the temporal translation and warping, as well as the variations in motion scales and execution rates. To address these challenges, we propose to treat the 3D human action recognition as a video-level hashing problem and propose a novel First-Take-All (FTA) Hashing algorithm capable of hashing the entire video into hash codes of fixed length. We demonstrate that this FTA algorithm produces a compact representation of the video invariant to the above mentioned variations, through which action recognition can be solved by an efficient nearest neighbor search by the Hamming distance between the FTA hash codes. Experiments on the public 3D human action datasets shows that the FTA algorithm can reach a recognition accuracy higher than 80%, with about 15 bits per frame considering there are 65 frames per video over the datasets.
An Elimination Method to Solve Interval Polynomial Systems
Venue: arXiv cs.SC 2015
Year: 2015

There are several efficient methods to solve linear interval polynomial systems in the context of interval computations, however, the general case of interval polynomial systems is not yet covered as well. In this paper we introduce a new elimination method to solve and analyse interval polynomial systems, in general case. This method is based on computational algebraic geometry concepts such as polynomial ideals and Groebner basis computation. Specially, we use the comprehensive Groebner system concept to keep the dependencies between interval coefficients. At the end of paper, we will state some applications of our method to evaluate its performance.
Uniform generation in trace monoids
Venue: arXiv cs.FL 2015
Year: 2015

We consider the problem of random uniform generation of traces (the elements of a free partially commutative monoid) in light of the uniform measure on the boundary at infinity of the associated monoid. We obtain a product decomposition of the uniform measure at infinity if the trace monoid has several irreducible components-a case where other notions such as Parry measures, are not defined. Random generation algorithms are then examined.
Deterministic Construction of RIP Matrices in Compressed Sensing from Constant Weight Codes
Venue: arXiv cs.IT 2015
Year: 2015

The expicit restricted isometry property (RIP) measurement matrices are needed in practical application of compressed sensing in signal processing. RIP matrices from Reed-Solomon codes, BCH codes, orthogonal codes, expander graphs have been proposed and analysised. On the other hand binary constant weight codes have been studied for many years and many optimal or near-optimal small weight and ditance constant weight codes have been determined. In this paper we propose a new deterministic construction of RIP measurement matrices in compressed sensing from binary and ternary contant weight codes. The sparse orders and the number of budged rows in the new constant-weight-code-based RIP matrices can be arbitrary. These contant-weight-code based RIP matrices have better parameters compared with the DeVore RIP matrices when the sizes are small.
Non-parametric Revenue Optimization for Generalized Second Price Auctions
Venue: arXiv cs.LG 2015
Year: 2015

We present an extensive analysis of the key problem of learning optimal reserve prices for generalized second price auctions. We describe two algorithms for this task: one based on density estimation, and a novel algorithm benefiting from solid theoretical guarantees and with a very favorable running-time complexity of $O(n S \log (n S))$, where $n$ is the sample size and $S$ the number of slots. Our theoretical guarantees are more favorable than those previously presented in the literature. Additionally, we show that even if bidders do not play at an equilibrium, our second algorithm is still well defined and minimizes a quantity of interest. To our knowledge, this is the first attempt to apply learning algorithms to the problem of reserve price optimization in GSP auctions. Finally, we present the first convergence analysis of empirical equilibrium bidding functions to the unique symmetric Bayesian-Nash equilibrium of a GSP.
Empirical Studies on Symbolic Aggregation Approximation Under Statistical Perspectives for Knowledge Discovery in Time Series
Venue: arXiv cs.LG 2015
Year: 2015

Symbolic Aggregation approXimation (SAX) has been the de facto standard representation methods for knowledge discovery in time series on a number of tasks and applications. So far, very little work has been done in empirically investigating the intrinsic properties and statistical mechanics in SAX words. In this paper, we applied several statistical measurements and proposed a new statistical measurement, i.e. information embedding cost (IEC) to analyze the statistical behaviors of the symbolic dynamics. Our experiments on the benchmark datasets and the clinical signals demonstrate that SAX can always reduce the complexity while preserving the core information embedded in the original time series with significant embedding efficiency. Our proposed IEC score provide a priori to determine if SAX is adequate for specific dataset, which can be generalized to evaluate other symbolic representations. Our work provides an analytical framework with several statistical tools to analyze, evaluate and further improve the symbolic dynamics for knowledge discovery in time series.
Self Organizing Maps Whose Topologies Can Be Learned With Adaptive Binary Search Trees Using Conditional Rotations
Venue: arXiv cs.NE 2015
Year: 2015

Numerous variants of Self-Organizing Maps (SOMs) have been proposed in the literature, including those which also possess an underlying structure, and in some cases, this structure itself can be defined by the user Although the concepts of growing the SOM and updating it have been studied, the whole issue of using a self-organizing Adaptive Data Structure (ADS) to further enhance the properties of the underlying SOM, has been unexplored. In an earlier work, we impose an arbitrary, user-defined, tree-like topology onto the codebooks, which consequently enforced a neighborhood phenomenon and the so-called tree-based Bubble of Activity. In this paper, we consider how the underlying tree itself can be rendered dynamic and adaptively transformed. To do this, we present methods by which a SOM with an underlying Binary Search Tree (BST) structure can be adaptively re-structured using Conditional Rotations (CONROT). These rotations on the nodes of the tree are local, can be done in constant time, and performed so as to decrease the Weighted Path Length (WPL) of the entire tree. In doing this, we introduce the pioneering concept referred to as Neural Promotion, where neurons gain prominence in the Neural Network (NN) as their significance increases. We are not aware of any research which deals with the issue of Neural Promotion. The advantages of such a scheme is that the user need not be aware of any of the topological peculiarities of the stochastic data distribution. Rather, the algorithm, referred to as the TTOSOM with Conditional Rotations (TTOCONROT), converges in such a manner that the neurons are ultimately placed in the input space so as to represent its stochastic distribution, and additionally, the neighborhood properties of the neurons suit the best BST that represents the data. These properties have been confirmed by our experimental results on a variety of data sets.
OMP2HMPP: Compiler Framework for Energy Performance Trade-off Analysis of Automatically Generated Codes
Venue: arXiv cs.DC 2015
Year: 2015

We present OMP2HMPP, a tool that, in a first step, automatically translates OpenMP code into various possible transformations of HMPP. In a second step OMP2HMPP executes all variants to obtain the performance and power consumption of each transformation. The resulting trade-off can be used to choose the more convenient version. After running the tool on a set of codes from the Polybench benchmark we show that the best automatic transformation is equivalent to a manual one done by an expert. Compared with original OpenMP code running in 2 quad-core processors we obtain an average speed-up of 31x and 5.86x factor in operations per watt.
Adversarial patrolling with spatially uncertain alarm signals
Venue: arXiv cs.AI 2015
Year: 2015

When securing complex infrastructures or large environments, constant surveillance of every area is not affordable. To cope with this issue, a common countermeasure is the usage of cheap but wide-ranged sensors, able to detect suspicious events that occur in large areas, supporting patrollers to improve the effectiveness of their strategies. However, such sensors are commonly affected by uncertainty. In the present paper, we focus on spatially uncertain alarm signals. That is, the alarm system is able to detect an attack but it is uncertain on the exact position where the attack is taking place. This is common when the area to be secured is wide such as in border patrolling and fair site surveillance. We propose, to the best of our knowledge, the first Patrolling Security Game model where a Defender is supported by a spatially uncertain alarm system which non-deterministically generates signals once a target is under attack. We show that finding the optimal strategy in arbitrary graphs is APX-hard even in zero-sum games and we provide two (exponential time) exact algorithms and two (polynomial time) approximation algorithms. Furthermore, we analyse what happens in environments with special topologies, showing that in linear and cycle graphs the optimal patrolling strategy can be found in polynomial time, de facto allowing our algorithms to be used in real-life scenarios, while in trees the problem is NP-hard. Finally, we show that without false positives and missed detections, the best patrolling strategy reduces to stay in a place, wait for a signal, and respond to it at best. This strategy is optimal even with non-negligible missed detection rates, which, unfortunately, affect every commercial alarm system. We evaluate our methods in simulation, assessing both quantitative and qualitative aspects.
Parity Decision Tree Complexity and 4-Party Communication Complexity of XOR-functions Are Polynomially Equivalent
Venue: arXiv cs.CC 2015
Year: 2015

In this note, we study the relation between the parity decision tree complexity of a boolean function $f$, denoted by $\mathrm{D}_{\oplus}(f)$, and the $k$-party number-in-hand multiparty communication complexity of the XOR functions $F(x_1,\ldots, x_k)= f(x_1\oplus\cdots\oplus x_k)$, denoted by $\mathrm{CC}^{(k)}(F)$. It is known that $\mathrm{CC}^{(k)}(F)\leq k\cdot\mathrm{D}_{\oplus}(f)$ because the players can simulate the parity decision tree that computes $f$. In this note, we show that \[\mathrm{D}_{\oplus}(f)\leq O\big(\mathrm{CC}^{(4)}(F)^5\big).\] Our main tool is a recent result from additive combinatorics due to Sanders. As $\mathrm{CC}^{(k)}(F)$ is non-decreasing as $k$ grows, the parity decision tree complexity of $f$ and the communication complexity of the corresponding $k$-argument XOR functions are polynomially equivalent whenever $k\geq 4$. Remark: After the first version of this paper was finished, we discovered that Hatami and Lovett had already discovered the same result a few years ago, without writing it up.
Reviewing Data Visualization: an Analytical Taxonomical Study
Venue: arXiv cs.GR 2015
Year: 2015

This paper presents an analytical taxonomy that can suitably describe, rather than simply classify, techniques for data presentation. Unlike previous works, we do not consider particular aspects of visualization techniques, but their mechanisms and foundational vision perception. Instead of just adjusting visualization research to a classification system, our aim is to better understand its process. For doing so, we depart from elementary concepts to reach a model that can describe how visualization techniques work and how they convey meaning.
Computational Extensive-Form Games
Venue: arXiv cs.GT 2015
Year: 2015

We define solution concepts appropriate for computationally bounded players playing a fixed finite game. To do so, we need to define what it means for a \emph{computational game}, which is a sequence of games that get larger in some appropriate sense, to represent a single finite underlying extensive-form game. Roughly speaking, we require all the games in the sequence to have essentially the same structure as the underlying game, except that two histories that are indistinguishable (i.e., in the same information set) in the underlying game may correspond to histories that are only computationally indistinguishable in the computational game. We define a computational version of both Nash equilibrium and sequential equilibrium for computational games, and show that every Nash (resp., sequential) equilibrium in the underlying game corresponds to a computational Nash (resp., sequential) equilibrium in the computational game. One advantage of our approach is that if a cryptographic protocol represents an abstract game, then we can analyze its strategic behavior in the abstract game, and thus separate the cryptographic analysis of the protocol from the strategic analysis.
License Plate Recognition System Based on Color Coding Of License Plates
Venue: arXiv cs.CV 2015
Year: 2015

License Plate Recognition Systems are used to determine the license plate number of a vehicle. The current system mainly uses Optical Character Recognition to recognize the number plate. There are several problems to this system. Some of them include interchanging of several letters or numbers (letter O with digit 0), difficulty in localizing the license plate, high error rate, use of different fonts in license plates etc. So a new system to recognize the license plate number using color coding of license plates is proposed in this paper. Easier localization of license plate can be done by searching for the start or stop patters of license plates. An eight segment display system along with traditional numbering with the first and last segments left for start or stop patterns is proposed in this paper. Practical applications include several areas under Internet of Things (IoT).
Increasing loyalty using predictive modeling in Business-to-Business Telecommunication
Venue: arXiv cs.OH 2015
Year: 2015

Customer Relationship Management (CRM) is a key element of modern marketing strategies. One of the most practical way to build useful knowledge on customers in a CRM system to produce scores to forecast churn behavior, propensity to subscribe to a new service... In AMEA zone (Asia, Middle East and Africa zone), the context of fierce competition may represent a higher percentage, and particularly in B2B market. But by contrast, to our knowledge, no scientific papers were dedicated and published to detail the way to improve loyalty in B2B Telco market. If we can assume at low segments similarities between B2B and B2C, some research is required in order to model B2B user behavior versus B2C behavior. This problematic stands actual as "Bring Your own Device" (BYOD) becomes more and more trendy. Answering business requirements, our team applied some B2C predictive tools with adapting them to B2B in an AMEA country Orange affiliate.
Students Exeat Monitoring System Using Fingerprint Biometric Authentication and Mobile Short Message Service
Venue: arXiv cs.CY 2015
Year: 2015

Exeat is a generic term commonly used to describe a period of absence from a centre of learning either for entire day, or parts of a day for appointments, interviews, open days and other fixtures in privately owned academic environment. The current method of monitoring students movement is inefficient and brings difficulty to the University Halls management checking students exit or entry into the halls of residence as well as impersonation. By using nexus combination of Ubiquitous Mobile Computing Technology through Mobile Short Message Service and biometric fingerprint approach exeat management and monitoring is quick and easy. Result after testing of the designed and simulated system shows that exeat monitoring systems is less prone to forgery as stakeholders are carried along, capable of preventing impersonation among students, and provide absolute electronic compliance to the policy of issuing exeat to students in the University Halls of Residence.
Meta-Packages: Painless Domain Specific Languages
Venue: arXiv cs.SE 2015
Year: 2015

Domain Specific Languages are used to provide a tailored modelling notation for a specific application domain. There are currently two main approaches to DSLs: standard notations that are tailored by adding simple properties; new notations that are designed from scratch. There are problems with both of these approaches which can be addressed by providing access to a small meta-language based on packages and classes. A meta-modelling approach based on meta-packages allows a wide range of DSLs to be defined in a standard way. The DSLs can be processed using standard object-based extension at the meta-level and existing tooling can easily be defined to adapt to the new languages. This paper introduces the concept of meta-packages and provides a simple example.
Designing a Global Authentication Infrastructure
Venue: arXiv cs.CR 2015
Year: 2015

We address the problem of scaling authentication for naming, routing, and end-entity certification to a global environment in which authentication policies and users' sets of trust roots vary widely. The current mechanisms for authenticating names (DNSSEC), routes (BGPSEC), and end-entity certificates (TLS) do not support a coexistence of authentication policies, affect the entire Internet when compromised, cannot update trust root information efficiently, and do not provide users with the ability to make flexible trust decisions. We propose a Scalable Authentication Infrastructure for Next-generation Trust (SAINT), which partitions the Internet into groups with common, local trust roots, and isolates the effects of a compromised trust root. SAINT requires groups with direct routing connections to cross-sign each other for authentication purposes, allowing diverse authentication policies while keeping all entities globally verifiable. SAINT makes trust root management a central part of the network architecture, enabling trust root updates within seconds and allowing users to make flexible trust decisions. SAINT operates without a significant performance penalty and can be deployed alongside existing infrastructures.
A Non-Oblivious Reduction of Counting Ones to Multiplication
Venue: arXiv cs.DS 2015
Year: 2015

An algorithm counting the number of ones in a binary word is presented running in time $O(\log\log b)$ where $b$ is the number of ones. The operations available include bit-wise logical operations and multiplication.
Test Set Diameter: Quantifying the Diversity of Sets of Test Cases
Venue: arXiv cs.SE 2015
Year: 2015

A common and natural intuition among software testers is that test cases need to differ if a software system is to be tested properly and its quality ensured. Consequently, much research has gone into formulating distance measures for how test cases, their inputs and/or their outputs differ. However, common to these proposals is that they are data type specific and/or calculate the diversity only between pairs of test inputs, traces or outputs. We propose a new metric to measure the diversity of sets of tests: the test set diameter (TSDm). It extends our earlier, pairwise test diversity metrics based on recent advances in information theory regarding the calculation of the normalized compression distance (NCD) for multisets. An advantage is that TSDm can be applied regardless of data type and on any test-related information, not only the test inputs. A downside is the increased computational time compared to competing approaches. Our experiments on four different systems show that the test set diameter can help select test sets with higher structural and fault coverage than random selection even when only applied to test inputs. This can enable early test design and selection, prior to even having a software system to test, and complement other types of test automation and analysis. We argue that this quantification of test set diversity creates a number of opportunities to better understand software quality and provides practical ways to increase it.
From Paraphrase Database to Compositional Paraphrase Model and Back
Venue: arXiv cs.CL 2015
Year: 2015

The Paraphrase Database (PPDB; Ganitkevitch et al., 2013) is an extensive semantic resource, consisting of a list of phrase pairs with (heuristic) confidence estimates. However, it is still unclear how it can best be used, due to the heuristic nature of the confidences and its necessarily incomplete coverage. We propose models to leverage the phrase pairs from the PPDB to build parametric paraphrase models that score paraphrase pairs more accurately than the PPDB's internal scores while simultaneously improving its coverage. They allow for learning phrase embeddings as well as improved word embeddings. Moreover, we introduce two new, manually annotated datasets to evaluate short-phrase paraphrasing models. Using our paraphrase model trained using PPDB, we achieve state-of-the-art results on standard word and bigram similarity tasks and beat strong baselines on our new short phrase paraphrase tasks.
Truthful Linear Regression
Venue: arXiv cs.GT 2015
Year: 2015

We consider the problem of fitting a linear model to data held by individuals who are concerned about their privacy. Incentivizing most players to truthfully report their data to the analyst constrains our design to mechanisms that provide a privacy guarantee to the participants; we use differential privacy to model individuals' privacy losses. This immediately poses a problem, as differentially private computation of a linear model necessarily produces a biased estimation, and existing approaches to design mechanisms to elicit data from privacy-sensitive individuals do not generalize well to biased estimators. We overcome this challenge through an appropriate design of the computation and payment scheme.
Amortized Rotation Cost in AVL Trees
Venue: arXiv cs.DS 2015
Year: 2015

An AVL tree is the original type of balanced binary search tree. An insertion in an $n$-node AVL tree takes at most two rotations, but a deletion in an $n$-node AVL tree can take $Θ(\log n)$. A natural question is whether deletions can take many rotations not only in the worst case but in the amortized case as well. A sequence of $n$ successive deletions in an $n$-node tree takes $O(n)$ rotations, but what happens when insertions are intermixed with deletions? Heaupler, Sen, and Tarjan conjectured that alternating insertions and deletions in an $n$-node AVL tree can cause each deletion to do $Ω(\log n)$ rotations, but they provided no construction to justify their claim. We provide such a construction: we show that, for infinitely many $n$, there is a set $E$ of {\it expensive} $n$-node AVL trees with the property that, given any tree in $E$, deleting a certain leaf and then reinserting it produces a tree in $E$, with the deletion having done $Θ(\log n)$ rotations. One can do an arbitrary number of such expensive deletion-insertion pairs. The difficulty in obtaining such a construction is that in general the tree produced by an expensive deletion-insertion pair is not the original tree. Indeed, if the trees in $E$ have even height $k$, $2^{k/2}$ deletion-insertion pairs are required to reproduce the original tree.